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» Ranking in Spatial Databases
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VLDB
1994
ACM
140views Database» more  VLDB 1994»
13 years 12 months ago
Efficient and Effective Clustering Methods for Spatial Data Mining
Spatial data mining is the discovery of interesting relationships and characteristics that may exist implicitly in spatial databases. In this paper, we explore whether clustering ...
Raymond T. Ng, Jiawei Han
DASFAA
2009
IEEE
133views Database» more  DASFAA 2009»
14 years 2 months ago
Probabilistic Ranking in Uncertain Vector Spaces
Abstract. In many application domains, e.g. sensor databases, traffic management or recognition systems, objects have to be compared based on positionally and existentially uncert...
Thomas Bernecker, Hans-Peter Kriegel, Matthias Ren...
SIGMOD
2007
ACM
181views Database» more  SIGMOD 2007»
14 years 8 months ago
Progressive and selective merge: computing top-k with ad-hoc ranking functions
The family of threshold algorithm (i.e., TA) has been widely studied for efficiently computing top-k queries. TA uses a sort-merge framework that assumes data lists are pre-sorted...
Dong Xin, Jiawei Han, Kevin Chen-Chuan Chang
SIGMOD
2007
ACM
172views Database» more  SIGMOD 2007»
14 years 8 months ago
Auditing disclosure by relevance ranking
Numerous widely publicized cases of theft and misuse of private information underscore the need for audit technology to identify the sources of unauthorized disclosure. We present...
Rakesh Agrawal, Alexandre V. Evfimievski, Jerry Ki...
SIGMOD
2011
ACM
234views Database» more  SIGMOD 2011»
12 years 10 months ago
Ranking with uncertain scoring functions: semantics and sensitivity measures
Ranking queries report the top-K results according to a user-defined scoring function. A widely used scoring function is the weighted summation of multiple scores. Often times, u...
Mohamed A. Soliman, Ihab F. Ilyas, Davide Martinen...